Associate Director, Data Science US Vaccines
MSDAbout the role
Job Description
Associate Director, Data Science - US Vaccines
The Associate Director Data Science will be responsible for developing and communicating data-driven and actionable insights that drive greater customer and market understanding to inform launch brand strategies, help meet in-line brand growth and commercial objectives.
This role requires the individual to be an independent contributor on the Business Insights & Analytics team as well as be a lead partner in helping to scope, design, and deliver well-defined advanced analytics solutions aligned to business priorities. The ideal candidate will partner with a cross functional insights team that spans data science, market research, data strategy, and measurement.
The preferred candidate should have intellectual curiosity, entrepreneurial spirit, consultative mindset, strong understanding of healthcare & pharma marketing. The person should be able to identify the data, analytics and research needs to define, enable, and inform commercial strategies of our brand and business leaders. This role will require interfacing and collaborating with many teams. Colleagues who will thrive in this role are motivated by developing a deep appreciation of pharma secondary data sources and possess an ability to define and translate objectives and business questions into analytical problems that require advanced and scalable solutions that produce actionable insights.
Primary Job Function and Key Responsibilities
Thoroughly appreciate the assigned internal stakeholder business needs and priorities to help build analyses promoting business objectives by delivering actionable insights
Mine and analyze data leveraging advanced analytical/statistical techniques from disparate databases/sources (claims data/EMR Data and other sources) to drive optimization and improvement of therapy area commercial business strategies
Be accountable for ensuring delivery of analyses with high quality standards, timeliness, compliance, and excellent user experience
Comprehend the complexity/dependencies between multiple teams, platforms (people, technologies)
Convey new trends/methodologies being implemented/considered within the company ecosystem and bring new ideas forward that will enhance analytic capabilities of the organization
Contribute to innovative experiments, specifically to idea generation, idea incubation and/or experimentation, identifying tangible and measurable criteria
Where applicable, partner throughout the organization to identify, work with and direct the sourcing of externally available data sources based on the business needs, and execution of specific business objectives
Effectively convey and positively influence stakeholders
Minimum required education:
A minimum of BS (or equivalent) in Data Science, Computer Science, Management Information Systems, IT, or an equivalent scientific/commercial discipline. MBA or Master’s or Doctorate degree in Decision Science, Marketing, Engineering, Public Health, Biological Sciences, Nursing, Pharmacy, Mathematics, Economy, Statistics, Computer Science, Medical Sciences is preferred.
Required Experience & Skills:
Work objectively and as a Team member with Integrity | Precision | Accomplishment | Motivational Ambition | Respect
Minimum of 3 plus years of relevant knowledge using data science to deliver measurable impact in commercial pharma landscape.
Knowledge in mining medical claims/EMR, social media, etc. data with a strategic/inquisitive mindset and proven record of being able to produce actionable business insights that drive positive commercial results
Providing actionable insights through analytics to commercial franchises brands at various stages of product life cycle (development, launch, maturity, end of life cycle)
Provide guidance, help define tactics and strategies to implement targeting and segmentation scheme using predictive and machine learning models
Ability to extract data from various database tables using tools such as SQL to develop features to be used in analysis including the ability to perform feature engineering
Knowledge in developing both machine learning and descriptive algorithms/modeling using such languages as Python, R etc.
Comfortable formulating actionable insights and recommendations from commercial analytics into presentations (using PowerPoint, Tableau, etc.) and presenting results to various levels of franchise management
Proven knowledge of business processes and industry/market trends within the pharmaceutical/healthcare space
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